JP2022026929A - Radiation image processing apparatus, method and program - Google Patents

Abstract

To properly suppress the granularity of a radiation image with low S/N in a radiation image processing apparatus, method and program.SOLUTION: A processor acquires a first radiation image and a second radiation image that include the same subject and have different S/N. The processor derives the processing content of the first granularity suppression processing on the first radiation image with high S/N out of the first radiation image and second radiation image, and derives the processing content of the second granularity suppression processing on the second radiation image on the basis of the processing content of the first granularity suppression processing. The processor performs the granularity suppression processing on the second radiation image on the basis of the processing content of the second granularity suppression processing.SELECTED DRAWING: Figure 3

Description

The present disclosure relates to radiographic image processing equipment, methods and programs.

Conventionally, energy subtraction using two radiation images obtained by irradiating a subject with two types of radiation having different energy distributions by utilizing the fact that the amount of radiation transmitted differs depending on the substance constituting the subject. The processing is known. The energy subtraction processing is a specific structure in which each pixel of the two radiation images obtained as described above is associated with each other, multiplied by an appropriate weighting factor between the pixels, and then subtracted (subtract). It is a method to acquire the extracted image. By performing such energy subtraction processing, for example, if a soft tissue image obtained by extracting the soft tissue from a radiographic image obtained by photographing the chest is derived, the shadow appearing on the soft tissue can be observed without being disturbed by the bone. .. On the contrary, if the bone image obtained by extracting the bone is derived, the shadow appearing on the bone can be observed without being disturbed by the soft tissue.

A one-shot method and a two-shot method are known as a method of photographing for performing energy subtraction processing (hereinafter, referred to as energy subtraction photographing). In the one-shot method, two radiation detectors for detecting radiation and acquiring a radiation image are superposed with a radiation energy conversion filter in between, and two radiation detections in which the radiation transmitted through the subject is superposed are superposed. This is a method in which two radiation detectors are irradiated with radiation having different energy distributions by irradiating the vessels at the same time. The two-shot method is a method in which photography is performed twice using two types of radiation having different energy distributions.

On the other hand, the radiation image has a problem that the graininess is deteriorated due to the influence of the quantum noise of radiation (hereinafter, simply referred to as noise) in the portion where the radiation dose is low and the density is low. Therefore, as an image process for a radiographic image, various methods for suppressing the grain contained in the radiographic image have been proposed. For example, a method has been proposed in which the amount of noise contained in a radiation image is estimated, the amount of noise is converted based on body thickness information, and the noise in the radiation image is removed based on the amount of converted noise to suppress graininess. (See, for example, Patent Document 1).

As the grain suppression process, a smoothing process using a smoothing filter that removes a frequency component corresponding to noise is well known. For example, in Patent Document 2, a radiographic image is frequency-converted to create a band image in which each represents a frequency component of a different frequency band, an edge direction of a pixel of interest to be processed in the band image is detected, and an edge is obtained. A method has been proposed in which a smoothing process is performed along a direction, a band image obtained by the smoothed band image is frequency-synthesized, and a processed radiographic image is acquired. By performing such a grain suppression process, it is possible to reduce the grain while preserving the edges contained in the radiographic image.

Japanese Unexamined Patent Publication No. 2015-167613 Japanese Unexamined Patent Publication No. 2002-133410

By the way, in the one-shot method of energy subtraction imaging, the radiation transmitted through the subject is simultaneously irradiated to two radiation detectors stacked with a radiation energy conversion filter interposed therebetween. Therefore, the radiation detector on the side far from the radiation source is irradiated with a smaller amount of radiation than the radiation detector on the side closer to the radiation source. Further, also in the case of the two-shot method, in order to reduce the exposure dose to the subject, the radiation dose is reduced in the second shooting as compared with the first shooting. Therefore, of the two radiographic images acquired by the energy subtraction processing, one radiographic image is more noisy than the other radiographic image (that is, the signal-to-noise ratio (S / N) is lower). .. In this case, by smoothing the radiographic image along the edge direction as described above, it is possible to suppress graininess while preserving the edges contained in the radiographic image.

However, in a noisy radiation image (hereinafter referred to as a low S / N radiation image), the amplitude of the signal value of the noise to be removed may be larger than the contrast of the edge to be preserved. Therefore, when the grain suppression process is performed on a low S / N radiation image, noise can be suppressed, but the contrast of the edge is lowered. As a result, it is not possible to achieve both noise suppression and edge preservation, and the edges are buried in the noise, so that the structure of the edges and the like included in the radiographic image cannot be restored.

The present disclosure has been made in view of the above circumstances, and an object of the present disclosure is to appropriately suppress graininess of a low S / N radiographic image.

The radiographic image processing apparatus according to the present disclosure comprises at least one processor.
The processor is
The first radiographic image and the second radiological image including the same subject but different S / N are acquired, and the second radiographic image is acquired.
Of the first radiographic image and the second radiographic image, the processing content of the first grain suppression treatment for the first radiographic image having a high S / N is derived.
Based on the processing content of the first granular suppression processing, the processing content of the second granular suppression processing for the second radiographic image is derived, and the processing content is derived.
The grain suppression process is configured to perform the grain suppression process on the second radiographic image based on the processing content of the second grain suppression process.

In the radiation image processing apparatus according to the present disclosure, the processing content of the second grain suppression processing performed on each pixel of the second radiation image is applied to each pixel of the second radiation image of the first radiation image. It may be the same as the processing content of the first grain suppression processing performed on the corresponding pixel.

Further, in the radiation image processing of the present embodiment, the processor is the first with respect to the pixel of interest based on the difference between the pixel value of the pixel of interest and the pixel value of the pixels surrounding the pixel of interest in the first radiation image. The processing area for performing the grain suppression treatment may be configured to be derived as the processing content of the first grain suppression treatment.

Further, in the radiographic image processing of the present embodiment, the processor may derive the weight for the pixels in the processing region as the processing content of the first grain suppression processing based on the difference.

Further, in the radiographic image processing of the present embodiment, the processing content may be the filter characteristics of the edge preservation smoothing filter.

Further, in the radiation image processing of the present embodiment, the processor derives a physical quantity map of the subject based on at least one of the first radiation image and the second radiation image.
It may be configured to derive the processing content of the first grain suppression process based on the physical quantity map.

Further, in the radiation image processing of the present embodiment, the first radiation image and the second radiation image may be acquired based on radiation having a different energy distribution for energy subtraction.

The radiation image processing method according to the present disclosure acquires a first radiation image and a second radiation image including the same subject but having different S / N.
Of the first radiographic image and the second radiographic image, the processing content of the first grain suppression treatment for the first radiographic image having a high S / N is derived.
Based on the processing content of the first granular suppression processing, the processing content of the second granular suppression processing for the second radiographic image is derived, and the processing content is derived.
The grain suppression process is performed on the second radiographic image based on the processing content of the second grain suppression process.

It should be noted that it may be provided as a program for causing a computer to execute the radiographic image processing method according to the present disclosure.

According to the present disclosure, graininess of a low S / N radiographic image can be appropriately suppressed.

Schematic configuration diagram of a radiation imaging system to which the radiation image processing apparatus according to the first embodiment of the present disclosure is applied. The figure which shows the schematic structure of the radiation image processing apparatus by 1st Embodiment. The figure which shows the functional structure of the radiation image processing apparatus by 1st Embodiment. The figure which shows the bilateral filter for the 1st radiation image. The figure which shows the local area of the 2nd radiation image corresponding to the local area of the 1st radiation image shown in FIG. Figure showing an example of a bilateral filter for a second radiographic image The figure which shows the soft tissue image and the bone image A flowchart showing the processing performed in the first embodiment. The figure which shows the functional structure of the radiation image processing apparatus by 2nd Embodiment. Diagram showing an example of a bilateral filter for a physical quantity map A flowchart showing the processing performed in the second embodiment.

Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. FIG. 1 is a schematic block diagram showing a configuration of a radiographic imaging system to which the radiographic image processing apparatus according to the embodiment of the present disclosure is applied. As shown in FIG. 1, the radiographic image photographing system according to the present embodiment includes an imaging device 1 and a radiographic image processing device 10 according to the present embodiment.

The photographing apparatus 1 irradiates the first radiation detector 5 and the second radiation detector 6 with radiation such as X-rays emitted from the radiation source 3 and transmitted through the subject H with different energies, respectively. This is a photographing device for performing energy subtraction by the shot method. At the time of photographing, as shown in FIG. 1, a first radiation detector 5, a radiation energy conversion filter 7 made of a copper plate or the like, and a second radiation detector 6 are arranged in order from the side closest to the radiation source 3. To drive the radiation source 3. The first and second radiation detectors 5 and 6 are in close contact with the radiation energy conversion filter 7.

As a result, in the first radiation detector 5, the first radiation image G1 of the subject H by low energy radiation including so-called soft rays is acquired. Further, in the second radiation detector 6, a second radiation image G2 of the subject H by high-energy radiation excluding soft lines is acquired. The first and second radiographic images are input to the radiographic image processing device 10. Both the first radiographic image G1 and the second radiographic image are front images including the chest and abdomen of the subject H.

The first and second radiation detectors 5 and 6 can repeatedly record and read a radiation image, and are so-called direct type radiation detectors that directly receive radiation and generate a charge. Or you may use a so-called indirect radiation detector that once converts the radiation into visible light and then converts the visible light into a charge signal. The radiation image signal reading method is a so-called TFT reading method in which the radiation image signal is read by turning the TFT (thin film transistor) switch on and off, or the radiation image signal by irradiating the read light. It is desirable to use a so-called optical readout method in which the above is read, but the present invention is not limited to this, and other ones may be used.

Next, the radiographic image processing apparatus according to the present embodiment will be described. First, with reference to FIG. 2, the hardware configuration of the radiographic image processing apparatus according to the present embodiment will be described. As shown in FIG. 2, the radiation image processing apparatus 10 is a computer such as a workstation, a server computer, and a personal computer, and has a CPU (Central Processing Unit) 11, a non-volatile storage 13, and a memory 16 as a temporary storage area. To prepare for. Further, the radiation image processing device 10 includes a display 14 such as a liquid crystal display, an input device 15 such as a keyboard and a mouse, and a network I / F (InterFace) 17 connected to the network 18. The CPU 11, the storage 13, the display 14, the input device 15, the memory 16, and the network I / F 17 are connected to the bus 18. The CPU 11 is an example of the processor in the present disclosure.

The storage 13 is realized by an HDD (Hard Disk Drive), an SSD (Solid State Drive), a flash memory, or the like. The storage 13 as a storage medium stores the radiation image processing program 12 installed in the radiation image processing device 10. The CPU 11 reads the radiation image processing program 12 from the storage 13, expands it in the memory 16, and executes the expanded radiation image processing program 12.

The radiation image processing program 12 is stored in a storage device of a server computer connected to the network or in a network storage in a state of being accessible from the outside, and is downloaded to a computer constituting the radiation image processing device 10 upon request. Will be installed. Alternatively, it is recorded and distributed on a recording medium such as a DVD (Digital Versatile Disc) or a CD-ROM (Compact Disc Read Only Memory), and the recording medium is installed in a computer constituting the radiation image processing apparatus 10.

Next, the functional configuration of the radiographic image processing apparatus according to the present embodiment will be described. FIG. 3 is a diagram showing a functional configuration of the radiographic image processing apparatus according to the present embodiment. As shown in FIG. 3, the radiation image processing apparatus 10 includes an image acquisition unit 20, a processing content derivation unit 21, a grain suppression processing unit 22, and a subtraction unit 23. Then, by executing the radiation image processing program 12, the CPU 11 functions as an image acquisition unit 20, a processing content derivation unit 21, a grain suppression processing unit 22, and a subtraction unit 23.

The image acquisition unit 20 causes the photographing device 1 to take a picture of the subject H, so that the first and second radiation detectors 5 and 6 can take a picture of the first radiation image G1 and the second radiation image G1 which is a front image of the subject H. Radiation image G2 of. When acquiring the first radiation image G1 and the second radiation image G2, the imaging conditions such as the irradiation dose of radiation, the tube voltage, and the SID (Source-to-Image receptor Distance) are set. Set. The set shooting conditions are stored in the storage 13.

The first and second radiographic images G1 and G2 may be acquired by a program separate from the radiographic image processing program of the present embodiment. In this case, the first and second radiation images G1 and G2 are stored in the storage 13, and the image acquisition unit 20 stores the first and second radiation images G1 and G2 stored in the storage 13 for processing. It will be read from 13.

The processing content derivation unit 21 derives the processing content of the first grain suppression process for the first radiation image G1, and based on the processing content of the first grain suppression process, the second radiation image G2 is second. Derivation of the processing content of the grain suppression process.

Here, in the present embodiment, the subject H is photographed by the one-shot method. In the case of the one-shot method, the radiation transmitted through the subject H is applied to the two radiation detectors 5 and 6 stacked with the radiation energy conversion filter 7 interposed therebetween. Therefore, the dose of the second radiation detector 6 on the side away from the radiation source 3 is smaller than that of the first radiation detector 5 on the side closer to the radiation source 3. As a result, the second radiation image G2 has more radiation quantum noise and a lower S / N than the first radiation image G1. Therefore, particularly for the second radiation image G2, it is necessary to perform a grain suppression process for suppressing the grain caused by the quantum noise.

The processing content derivation unit 21 derives the processing content of the first granular suppression processing for the first radiation image G1 having a high S / N among the first radiation image G1 and the second radiation image G1. Then, the processing content derivation unit 21 derives the processing content of the second granular suppression processing for the second radiographic image G2 based on the processing content of the first granular suppression processing. Hereinafter, the derivation of the processing content will be described.

Examples of the grain suppression process include a filtering process using a smoothing filter such as a Gaussian filter having a predetermined size such as 3 × 3 or 5 × 5 centered on the pixel of interest. However, if a Gaussian filter is used, the edges of the structures contained in the first and second radiographic images G1 and G2 may be blurred. Therefore, in the present embodiment, the grain suppression process is performed by using an edge preservation smoothing filter that suppresses grain while preventing edge blurring. The edge-preserving smoothing filter weights a normal distribution in which the weight of a pixel adjacent to the pixel of interest decreases as the distance from the pixel of interest increases, and the weight decreases as the difference in pixel value from the pixel of interest increases. Use a lateral filter.

FIG. 4 is a diagram showing an example of a bilateral filter for the first radiographic image G1. Note that FIG. 4 shows two local regions A1 of 5 × 5 pixels in the vicinity of the edge included in the first radiographic image G1 side by side. Further, the two local regions A1 shown in FIG. 4 are the same, but the positions of the pixels of interest are different from each other. In the local region A1 on the left side of FIG. 4, the low-density pixel in contact with the boundary of the edge is the pixel of interest P11. As described above, the bilateral filter weights the pixels adjacent to the pixel of interest so that the weight becomes smaller as the distance from the pixel of interest increases, and the weight decreases as the difference in pixel value from the pixel of interest increases. It is something to do.

Therefore, the processing content derivation unit 21 determines the filter size of the bilateral filter based on the difference between the pixel value of the pixel of interest and the pixel value of the pixels around the pixel of interest. For example, the smaller the difference between the pixel value of the pixel of interest and the pixel value around the pixel of interest, the larger the filter size. The size of the bilateral filter is an example of the processing area of the present disclosure. Further, the processing content derivation unit 21 determines the weight of the bilateral filter based on the difference between the pixel value of the pixel of interest and the pixel value of the pixels of the pixels around the pixel of interest. For example, the smaller the difference between the pixel value of the pixel of interest and the pixel value around the pixel of interest, the greater the weight of the pixel closer to the pixel of interest than the weight of the pixel away from the pixel of interest.

As a result, the processing content derivation unit 21 first uses a 3 × 3 bilateral filter F11 having a weight as shown on the left side of FIG. 4 with respect to the pixel P11 of interest in the local region A1 on the left side of FIG. Derived as the processing content of the grain suppression process.

In the local region A1 on the right side of FIG. 4, the high-density pixel in contact with the boundary of the edge is the pixel of interest P12. Therefore, the processing content derivation unit 21 first uses a 3 × 3 bilateral filter F12 having a weight as shown on the right side of FIG. 4 with respect to the pixel P12 of interest in the local region A1 on the right side of FIG. Derived as the processing content of the grain suppression process.

FIG. 5 is a diagram showing a local region A2 of a second radiographic image corresponding to a local region A1 of the first radiographic image shown in FIG. Note that FIG. 5 shows a local region A2 of 5 × 5 pixels in the vicinity of the edge included in the second radiographic image G2. The local region A2 is a region at the same position as the local region A1 in the first radiographic image G1 shown in FIG. The two local regions A2 shown in FIG. 5 are the same, but the positions of the pixels of interest are different from each other. In the local region A2 on the left side of FIG. 5, the pixel corresponding to the pixel of interest P11 shown in the local region A1 on the left side of FIG. 4 is the pixel of interest P21. In the local region A2 on the right side of FIG. 5, the pixel corresponding to the pixel of interest P12 shown in the local region A1 on the right side of FIG. 4 is the pixel of interest P22.

Here, the dose of radiation emitted to the second radiation detector 6 from which the second radiation image G2 is acquired is lower than that from the first radiation detector 5 from which the first radiation image G1 is acquired. .. Therefore, the second radiation image G2 has more radiation quantum noise than the first radiation image G1 and has poor graininess, so that the edges do not appear clearly. Further, due to the influence of quantum noise, low-density pixels may be included in the high-density region near the edge boundary, or high-density pixels may be included in the low-density region. Therefore, unlike the first radiation image G1, it is not possible to appropriately determine a bilateral filter that suppresses graininess while preserving edges from the second radiation image G2.

In this case, it is conceivable to use a smoothing filter such as a Gaussian filter. However, when such a smoothing filter is used, it is not possible to achieve both noise suppression and edge preservation, and as a result, the edges are buried in the noise, and the structure included in the second radiation image G2. Edges cannot be restored.

Therefore, in the present embodiment, the processing content deriving unit 21 processes the second granular suppression processing for the second radiographic image based on the processing content of the first granular suppression processing for the first radiographic image G1. Derive the content. That is, the processing content derivation unit 21 transfers the processing content of the second grain suppression processing performed on each pixel of the second radiation image G2 to each pixel of the second radiation image G2 of the first radiation image G1. The processing content of the second grain suppression processing is derived so as to be the same as the processing content of the first grain suppression processing performed on the corresponding pixel. Specifically, the processing content derivation unit 21 uses a bilateral filter having the same size and the same weight as the bilateral filter determined for each pixel of the first radiation image G1 to obtain a second radiation image. It is derived as the processing content of the second grain suppression processing for G2.

FIG. 6 is a diagram showing an example of a bilateral filter for the second radiographic image. Note that FIG. 6 shows a local region A2 of 5 × 5 pixels in the vicinity of the edge included in the second radiographic image G2, as in FIG. As shown in FIG. 6, the processing content derivation unit 21 refers to the attention pixel P21 in the local region A2 of the second radiation image G2 with respect to the attention pixel P11 in the local region A1 of the first radiation image G1. A bilateral filter F21 having the same size and the same weight as the derived bilateral filter F11 is derived as the processing content of the second grain suppression process.

Further, for the attention pixel P22 in the local region A2 of the second radiation image G2, the processing content derivation unit 21 is derived bilateral with respect to the attention pixel P12 in the local region A1 of the first radiation image G1. A bilateral filter F22 having the same size and the same weight as the filter F12 is derived as the processing content of the second grain suppression process.

In deriving the processing content of the second grain suppression process, it is necessary to associate the pixel positions of the first radiation image G1 and the second radiation image G2. Therefore, it is preferable to align the first radiation image G1 and the second radiation image G2.

The granular suppression processing unit 22 performs granular suppression processing on the first radiation image G1 and the second radiation image G2. That is, based on the processing content derived by the processing content deriving unit 21, the first radiation image G1 and the second radiation image G2 are subjected to grain suppression processing. Specifically, the first radiation image G1 is filtered by the bilateral filter derived for the first radiation image G1. Further, the second radiation image G2 is filtered by a bilateral filter derived based on the first radiation image G1.

The subtraction unit 23 performs subtraction processing on the first radiation image G1 and the second radiation image G2 to which the grain suppression processing has been performed according to the following equations (1) and (2), whereby the subject H The soft part image Gs from which the soft part is extracted and the bone part image Gb from which the bone part is extracted are derived. In equations (1) and (2), α and β are weighting coefficients.

Gs (x, y) = α · G2 (x, y) -G1 (x, y) (1)
Gb (x, y) = β · G2 (x, y) -G1 (x, y) (2)

FIG. 7 is a diagram showing a soft tissue image and a bone image. As shown in FIG. 7, in the soft tissue image Gs, the soft tissue in the subject H is extracted. Further, in the bone portion image Gb, the bone portion in the subject H is extracted. The generated soft tissue image Gs and bone image Gb are stored in the storage 13 or displayed on the display 14.

Next, the processing performed in the first embodiment will be described. FIG. 8 is a flowchart showing the processing performed in the first embodiment. It is assumed that the first and second radiographic images G1 and G2 are acquired by photographing and stored in the storage 13. When an instruction to start processing is input from the input device 15, the image acquisition unit 20 acquires the first and second radiation images G1 and G2 from the storage 13 (step ST1). Next, the processing content derivation unit 21 first derives the processing content of the first grain suppression process for the first radiographic image G1 (step ST2). Then, the processing content derivation unit 21 derives the processing content of the second granular suppression processing for the second radiographic image G2 based on the processing content of the first granular suppression processing (step ST3).

Next, the granular suppression processing unit 22 performs granular suppression processing on the first radiation image G1 and the second radiation image (step ST4). Then, the subtraction unit 23 performs the subtraction process according to the above equations (1) and (2) (step ST5). As a result, the soft tissue image Gs and the bone image Gb are derived. The derived soft tissue image Gs and bone image Gb are stored in the storage 13 (step ST6), and the process is terminated. In addition, instead of or in addition to storing the soft part image Gs and the bone part image Gb, the soft part image Gs and the bone part image Gb may be displayed on the display 14.

As described above, in the present embodiment, the processing content of the first grain suppression process for the first radiation image G1 is derived, and the processing content of the first particle suppression process is used for the second radiation image G2. The processing content of the second grain suppression process is derived. Here, the first radiation image G1 has a higher edge contrast and less noise than the second radiation image G2. Therefore, if the grain suppression process is performed on the first radiation image G1 based on the processing content of the first grain suppression process, the grain can be suppressed while preserving the edges. On the other hand, the second radiation image G2 has a lot of noise and the graininess is not so good. While preserving the edges corresponding to the radiation image G1, graininess can be suppressed so that the edges are not buried in noise. Therefore, the graininess of the low S / N radiographic image can be appropriately suppressed.

Next, a second embodiment of the present disclosure will be described. FIG. 9 is a diagram showing a functional configuration of the radiographic image processing apparatus according to the second embodiment of the present disclosure. In FIG. 9, the same reference numbers are assigned to the same configurations as those in FIG. 3, and detailed description thereof will be omitted here. The radiation image processing apparatus 10A according to the second embodiment further includes a map deriving unit 24 for deriving a physical quantity map of the subject H based on at least one of the first radiation image G1 and the second radiation image G2, and processes the radiation image processing apparatus 10A. The content derivation unit 21 is different from the first embodiment in that the processing content of the second grain suppression process for the second radiographic image G2 is derived based on the physical quantity map.

The map derivation unit 24 derives a physical quantity for the subject H. Examples of the physical quantity include the body thickness and bone density of the subject H. SID may be used as a physical quantity corresponding to the body thickness. Here, a case where the body thickness is derived as a physical quantity will be described. The map derivation unit 24 derives the body thickness of the subject H for each pixel of the first and second radiographic images G1 and G2 based on at least one of the first and second radiographic images G1 and G2. Since the body thickness is derived for each pixel of the first and second radiation images G1 and G2, the map derivation unit 24 derives the body thickness distribution in at least one of the first and second radiation images G1 and G2. It will be. When deriving the body thickness, the map deriving unit 24 uses the first radiation image G1 acquired by the radiation detector 5 on the side close to the subject H. However, the second radiographic image G2 may be used. In addition, regardless of which image is used, a low-frequency image representing the low-frequency component of the image may be derived, and the body thickness may be derived using the low-frequency image.

In the second embodiment, the map derivation unit 24 assumes that the brightness distribution in the first radiation image G1 matches the distribution of the body thickness of the subject H, and sets the pixel value of the first radiation image G1. The body thickness of the subject H is derived by converting it into a thickness using the attenuation coefficient in the soft portion of the subject H. Instead of this, a sensor may be provided in the photographing apparatus 1 and the thickness of the subject H may be measured using the sensor. Further, the map derivation unit 24 may derive the body thickness by approximating the body thickness of the subject H with a model such as a cube or an elliptical pillar. Further, the map derivation unit 24 may derive the body thickness of the subject H by any method such as the method described in Japanese Patent Application Laid-Open No. 2015-043959.

When deriving the bone mineral amount as a physical quantity, the map deriving unit 24 derives the bone mineral amount by using, for example, the method described in JP-A-2019-209027. When the method described in JP-A-2019-209027 is used, the map derivation unit 24 uses the above formula (2) from the first radiation image G1 and the second radiation image G2 before the grain suppression treatment. , Bone image Gb is derived. Then, the map deriving unit 24 derives the amount of bone mineral by converting each pixel of the bone image Gb into a pixel value of the bone image when acquired under the reference imaging conditions. Specifically, the map derivation unit 24 corrects each pixel value of the bone image Gb by using a predetermined correction coefficient for converting the pixel value of the bone image into the bone mineral amount. Derive the amount of bone mineral.

Here, the contrast of the structure included in the image of the radiation image to be grain-suppressed varies depending on the imaging conditions. Therefore, when performing edge preservation smoothing processing using a bilateral filter, it is necessary to control the intensity of the edge to be preserved according to the shooting conditions. On the other hand, in the body thickness map and the bone mineral content map showing the body thickness of the subject H, the contrast of the structure contained in the map is the thickness (mm) or the bone mineral content (g / cm ² ) that does not depend on the shooting conditions. Represented by.

Therefore, in the second embodiment, the processing content derivation unit 21 derives the processing content of the first grain suppression process for the first radiographic image G1 based on the physical quantity map. FIG. 10 is a diagram showing an example of a bilateral filter for a physical quantity map. Note that FIG. 10 shows two 5 × 5 pixel local regions A3 near the edges included in the physical quantity map side by side. The two local regions A3 shown in FIG. 10 are the same, but the positions of the pixels of interest are different from each other. In the local region A3 on the left side of FIG. 10, a high-density pixel on the edge is a pixel of interest P31. Therefore, for the pixel P31 of interest in the local region A3 on the left side of FIG. 10, the 3 × 3 bilateral filter F31 having a weight as shown on the left side of FIG. 10 is the processing content of the first grain suppression process. Is derived as.

In the local region A3 on the right side of FIG. 10, the low-density pixel in contact with the boundary of the edge is the pixel of interest P32. Therefore, for the pixel P32 of interest in the local region A3 on the right side of FIG. 10, the 3 × 3 bilateral filter F32 having a weight as shown on the right side of FIG. 10 is the processing content of the first grain suppression process. Is derived as.

Also in the second embodiment, the processing content derivation unit 21 applies the same bilateral filter as the bilateral filter determined for each pixel of the first radiation image G1 to the second radiation image G2. Derived as the processing content of the grain suppression process. That is, in the second radiation image G2, in the local region corresponding to the local region A3 of the first radiation image G1, the pixels corresponding to the attention pixels P31 in the local region A3 are the same as the bilateral filter F31. A bilateral filter having the same size and the same weight is derived as the processing content of the second grain suppression processing. Further, in the second radiation image G2, a bilateral filter having the same size and the same weight as the bilateral filter F32 is provided for the pixel corresponding to the pixel of interest P32 in the local region A3 of the first radiation image G1. , Derived as the processing content of the second grain suppression process.

Next, the processing performed in the second embodiment will be described. FIG. 11 is a flowchart showing the processing performed in the second embodiment. It is assumed that the first and second radiographic images G1 and G2 are acquired by photographing and stored in the storage 13. When an instruction to start processing is input from the input device 15, the image acquisition unit 20 acquires the first and second radiation images G1 and G2 from the storage 13 (step ST11). Next, the map deriving unit 24 derives a physical quantity map of the subject H based on at least one of the first radiation image G1 and the second radiation image G2 (step ST12).

Next, the processing content derivation unit 21 first derives the processing content of the first grain suppression process for the first radiation image G1 based on the physical quantity map (step ST13). Then, the processing content derivation unit 21 derives the processing content of the second granular suppression processing for the second radiographic image G2 based on the processing content of the first granular suppression processing (step ST14).

Next, the granular suppression processing unit 22 performs granular suppression processing on the first radiation image G1 and the second radiation image (step ST15). Then, the subtraction unit 23 performs the subtraction process according to the above equations (1) and (2) (step ST16). As a result, the soft tissue image Gs and the bone image Gb are derived. The derived soft tissue image Gs and bone image Gb are stored in the storage 13 (step ST17), and the process is terminated. In addition, instead of or in addition to storing the soft part image Gs and the bone part image Gb, the soft part image Gs and the bone part image Gb may be displayed on the display 14.

Here, in the first and second radiation images G1 and G2 to be grain-suppressed, the contrast of the structure included in the image varies depending on the imaging conditions. Therefore, in the case of performing edge preservation smoothing processing using a bilateral filter, if there is a structure to be preserved without smoothing, it is necessary to adjust the strength of the edge to be preserved according to the shooting conditions. On the other hand, in the body thickness map showing the body thickness of the subject H or the bone mineral amount map showing the bone mass of the subject H, the pixel value is represented by the thickness (mm) or the bone mineral amount (g / cm ² ). , The contrast of the structure contained in the map does not change depending on the shooting conditions. Therefore, if there is a structure that you want to save without smoothing, you can set the edge strength to save based on a value that does not depend on the imaging conditions such as the difference in body thickness or bone density between the structure you want to save and the surrounding structure. .. For example, when it is desired to retain a signal of a blood vessel structure having a diameter of 1 mm, if a body thickness map is used, the edge strength to be preserved may be set so as to preserve the structure having a body thickness difference of 1 mm or more from the periphery.

In the second embodiment, the physical quantity map of the subject H is derived, and the processing content of the second grain suppression process for the second radiation image G2 is derived based on the physical quantity map. Therefore, the processing contents of the first grain suppression process and the second grain suppression process can be derived without being affected by the change in the contrast of the structure in the image due to the change in the photographing conditions.

In each of the above embodiments, a bilateral filter is used as the edge preservation smoothing filter, but the present invention is not limited to this. Edges are also preserved by performing grain suppression using the Non-Local Means Filter, which weights based on the similarity between the pixel of interest on the image and the neighborhood of any pixel. At the same time, graininess can be suppressed.

Further, in each of the above embodiments, a filtering process using an edge preservation smoothing filter is performed as a grain suppression process, but the present invention is not limited to this. In the first radiation image G1, one or more pixels within a predetermined distance from the pixel of interest and the difference from the pixel value of the pixel of interest is equal to or greater than a predetermined threshold value are specified, and the pixel of interest and the specification are specified. The smoothing process for the pixels may be derived as the processing content of the first grain suppression process. In this case, in the second radiation image G2, the processing content of the second grain suppression process may be derived so as to smooth the pixel of interest and the specified image.

Also. In each of the above embodiments, the grain suppression process is performed by a filtering process, but the present invention is not limited to this. A function such as a mathematical formula for performing the granular suppression processing is derived as the processing content of the granular suppression processing, and the derived function is used to perform the granular suppression processing on the first and second radiographic images G1 and G2. You may do it.

Further, in each of the above embodiments, the grain suppression treatment is performed on the first radiation image G1 and the second radiation image G2, but the present invention is not limited to this. By performing multiple resolution conversion such as wavelet conversion on the first radiation image G1 and the second radiation image G2, a plurality of band images having different frequency bands are generated, and the band image of each frequency band is the first. The processing content of the granular suppression processing 1 and the processing content of the second granularity suppression processing are derived, and the first granularity is obtained for each frequency band image of the first and second radial images G1 and G2, respectively. The first and second radiographic images G1 and G2 that have undergone the grain suppression process may be derived by performing the suppression process and the second grain suppression process and frequency-synthesizing the band images after the process.

Further, in each of the above embodiments, the first and second radiographic images G1 and G2 are acquired by the one-shot method, but the first and second radiographic images G1 are obtained by the so-called two-shot method in which imaging is performed twice. , G2 may be acquired.

In the case of the two-shot method, in order to reduce the exposure dose to the subject H, the radiation dose is reduced at the time of the second shooting by the time of the first shooting. Therefore, of the first and second radiation images G1 and G2, one of the radiation images (here, the second radiation image G2) has more noise than the first radiation image G1. Therefore, even when the first and second radiographic images G1 and G2 are acquired by the two-shot method, the processing content of the second grain suppression treatment for the second radiographic image G2 is the same as in the above embodiment. It may be derived based on the processing content of the first grain suppression process for the first radiation image G1.

In the case of the two-shot method, the position of the subject H included in the first radiation image G1 and the second radiation image G2 may shift due to the body movement of the subject H. Therefore, in the first radiation image G1 and the second radiation image G2, it is preferable to perform the processing of the present embodiment after aligning the subjects. As the alignment process, for example, the method described in Japanese Patent Application Laid-Open No. 2011-255060 can be used. The method described in JP-A-2011-255060 is a plurality of first band images and a plurality of second band images representing structures having different frequency bands for each of the first and second radiographic images G1 and G2. Band images are generated, the amount of positional deviation of the positions corresponding to each other in the first band image and the second band image of the corresponding frequency band is acquired, and the first radiation image G1 and The alignment with the second radiation image G2 is performed.

Further, in the above embodiment, energy subtraction processing is performed using the radiation image acquired in the system for capturing the radiation image of the subject H using the first and second radiation detectors 5 and 6. However, it goes without saying that the present disclosure can also be applied when the first and second radiation images G1 and G2 are acquired by using the accumulative phosphor sheet instead of the radiation detector. In this case, two accumulative phosphor sheets are overlapped and irradiated with radiation transmitted through the subject H, and the radiation image information of the subject H is accumulated and recorded on each accumulator phosphor sheet, and the radiation image information of the subject H is accumulated and recorded on each accumulator phosphor sheet. The first and second radiographic images G1 and G2 may be acquired by reading the radiographic image information photoelectrically. The two-shot method may also be used when the first and second radiographic images G1 and G2 are acquired by using the accumulative phosphor sheet.

Further, the radiation in each of the above embodiments is not particularly limited, and α rays, γ rays and the like can be applied in addition to X-rays.

Further, in the above embodiment, for example, the hardware of the processing unit (Processing Unit) that executes various processes such as the image acquisition unit 20, the processing content derivation unit 21, the grain suppression processing unit 22, the subtraction unit 23, and the map derivation unit 24. As the structure, various processors (Processors) shown below can be used. As described above, the various processors include CPUs, which are general-purpose processors that execute software (programs) and function as various processing units, as well as circuits after manufacturing FPGAs (Field Programmable Gate Arrays) and the like. Dedicated electricity, which is a processor with a circuit configuration specially designed to execute specific processing such as Programmable Logic Device (PLD), which is a processor whose configuration can be changed, and ASIC (Application Specific Integrated Circuit). Circuits etc. are included.

One processing unit may be composed of one of these various processors, or a combination of two or more processors of the same type or different types (for example, a combination of a plurality of FPGAs or a combination of a CPU and an FPGA). ) May be configured. Further, a plurality of processing units may be configured by one processor.

As an example of configuring a plurality of processing units with one processor, first, as represented by a computer such as a client and a server, one processor is configured by a combination of one or more CPUs and software. There is a form in which this processor functions as a plurality of processing units. Second, as typified by System On Chip (SoC), there is a form that uses a processor that realizes the functions of the entire system including multiple processing units with one IC (Integrated Circuit) chip. be. As described above, the various processing units are configured by using one or more of the above-mentioned various processors as a hardware-like structure.

Further, as the hardware structure of these various processors, more specifically, an electric circuit (Circuitry) in which circuit elements such as semiconductor elements are combined can be used.

1 Imaging device 3 Radioactive source 5, 6 Radiation detector 7 Radiation energy conversion filter 10 Radiation image processing device 11 CPU
12 Radiation image processing program 13 Storage 14 Display 15 Input device 16 Memory 17 Network I / F
18 Bus 20 Image acquisition unit 21 Processing content derivation unit 22 Granular suppression processing unit 23 Subtraction unit 24 Map derivation unit A1, A2, A3 Local region F11, F12, F21, F22, F31, F32 Bilateral filter G1 First radiation image G2 Second radiation image Gb Bone image Gs Soft image P11, P12, P21, P22, P31, P32 Pixel of interest

Claims (9)

Equipped with at least one processor
The processor
The first radiographic image and the second radiological image including the same subject but different S / N are acquired, and the second radiographic image is acquired.
Of the first radiographic image and the second radiographic image, the processing content of the first grain suppression treatment for the first radiographic image having a high S / N is derived.
Based on the processing content of the first granular suppression treatment, the processing content of the second granular suppression processing for the second radiographic image is derived.
A radiation image processing apparatus configured to perform a grain suppression process on the second radiation image based on the processing content of the second grain suppression process. The processing content of the second grain suppression process performed on each pixel of the second radiation image is the pixel corresponding to each pixel of the second radiation image of the first radiation image. The radiographic image processing apparatus according to claim 1, which is the same as the processing content of the first grain suppression processing. The processor performs the first grain suppression processing on the attention pixel based on the difference between the pixel value of the pixel of interest and the pixel value of the pixels around the pixel of interest in the first radiation image. The radiographic image processing apparatus according to claim 1 or 2, which is configured to derive the above as the processing content of the first grain suppression processing. The radiographic image processing apparatus according to claim 3, wherein the processor derives a weight for a pixel in the processing region as a processing content of the first grain suppression processing based on the difference. The radiographic image processing apparatus according to any one of claims 1 to 4, wherein the processing content is a filter characteristic of an edge preservation smoothing filter. The processor derives a physical quantity map of the subject based on at least one of the first radiation image and the second radiation image.
The radiographic image processing apparatus according to any one of claims 1 to 5, which is configured to derive the processing content of the first grain suppression processing based on the physical quantity map. The radiographic image processing apparatus according to any one of claims 1 to 6, wherein the first radiographic image and the second radiographic image are acquired based on radiation having a different energy distribution for energy subtraction. The first radiographic image and the second radiological image including the same subject but different S / N are acquired, and the second radiographic image is acquired.
Of the first radiographic image and the second radiographic image, the processing content of the first grain suppression treatment for the first radiographic image having a high S / N is derived.
Based on the processing content of the first granular suppression treatment, the processing content of the second granular suppression processing for the second radiographic image is derived.
A radiation image processing method for performing a grain suppression process on the second radiation image based on the processing content of the second grain suppression process. The procedure for acquiring the first radiographic image and the second radiological image including the same subject but different S / N, and
A procedure for deriving the processing content of the first grain suppression treatment for the first radiographic image having a high S / N among the first radiographic image and the second radiographic image, and a procedure for deriving the processing content.
A procedure for deriving the processing content of the second granularity suppressing treatment for the second radiographic image based on the processing content of the first granularity suppressing treatment, and
A radiation image processing program that causes a computer to execute a procedure for performing a grain suppression process on the second radiation image based on the processing content of the second grain suppression process.

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